Proceedings of the 2nd International Conference on Information, Electronics and Computer

Research on Fuzzy Association Classification Algorithm for Large Transaction Database Based on SVM

Authors
Wen-qi Wang, Qiang Li
Corresponding Author
Wen-qi Wang
Available Online March 2014.
DOI
https://doi.org/10.2991/icieac-14.2014.3How to use a DOI?
Keywords
classification; decision tree;SVM; eigenvector;
Abstract
Aiming at the defects of inefficiency and hard classification boundary in large transaction database classification, A. fuzzy associative classification algorithm based on SVM was proposed, SVM input eigenvector was constructed by weighed index and compatibility measure of fuzzy associative classification role, the effect of quantitative attribute discretization on association classifier was effectively reduced. With reference to decision tree classification algorithm, linear kernel function was used to make the speed of classification because of classification of the test samples are not complete decision tree traversal, and adjustment of parameters when used the nonlinear kernel function was avoided. Experimental results verify the feasibility and effectiveness of the algorithm.
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Proceedings
2nd International Conference on Information, Electronics and Computer
Part of series
Advances in Intelligent Systems Research
Publication Date
March 2014
ISBN
978-90-78677-99-4
ISSN
1951-6851
DOI
https://doi.org/10.2991/icieac-14.2014.3How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Wen-qi Wang
AU  - Qiang Li
PY  - 2014/03
DA  - 2014/03
TI  - Research on Fuzzy Association Classification Algorithm for Large Transaction Database Based on SVM
BT  - 2nd International Conference on Information, Electronics and Computer
PB  - Atlantis Press
SN  - 1951-6851
UR  - https://doi.org/10.2991/icieac-14.2014.3
DO  - https://doi.org/10.2991/icieac-14.2014.3
ID  - Wang2014/03
ER  -